Generation of LR parsers by partial evaluation

The combination of modern programming languages and partial evaluation yields new approaches to old problems. In particular, the combination of functional programming and partial evaluation can turn a general parser into a parser generator. We use an inherently functional approach to implement general LR(k) parsers and specialize them with respect to the input grammars using offline partial evaluation. The functional specification of LR parsing yields a concise implementation of the algorithms themselves. Furthermore, we demonstrate the elegance of the functional approach by incorporating on-the-fly attribute evaluation for S-attributed grammars and two schemes for error recovery, which lend themselves to natural and elegant implementation. The parsers require only minor changes to achieve good specialization results. The generated parsers have production quality and match those produced by traditional parser generators in speed and compactness.